Generalizing Local and Non-Local Word-Reordering Patterns for Syntax-Based Machine Translation
نویسندگان
چکیده
Syntactic word reordering is essential for translations across different grammar structures between syntactically distant languagepairs. In this paper, we propose to embed local and non-local word reordering decisions in a synchronous context free grammar, and leverages the grammar in a chartbased decoder. Local word-reordering is effectively encoded in Hiero-like rules; whereas non-local word-reordering, which allows for long-range movements of syntactic chunks, is represented in tree-based reordering rules, which contain variables correspond to sourceside syntactic constituents. We demonstrate how these rules are learned from parallel corpora. Our proposed shallow Tree-to-String rules show significant improvements in translation quality across different test sets.
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